Depression

[Artificial intelligence and psychiatry: questions from psychiatrists to ChatGPT].

Psychiatrists and psychotherapists specialising in the fields of addiction, personality disorders, ADHD and suicidal crisis, we questioned the ChatGPT artificial intelligence program in order to form an opinion on the quality of its answers to questions on these subjects. Our aim is to satisfy our curiosity about these emerging tools. On the other hand, we want to assess the relevance of the answe...

Statistical and artificial intelligence techniques to identify risk factors for suicide in children and adolescents.

BACKGROUND: Suicidal Behaviors and Thoughts are a relevant public health issue that includes suicidal ideation, non-suicidal self-harm, attempted suicide, and failed suicides. Since there is a progression of suicidal behaviors, whereby suicide is more likely to be completed if there have already been previous behaviors or attempts to harm oneself, WHO has highlighted the need to detect early predi...

Interpretable Estimation of Suicide Risk and Severity from Complete Blood Count Parameters with Explainable Artificial Intelligence Methods.

BACKGROUND: The peripheral inflammatory markers are important in the pathophysiology of suicidal behavior. However, methods for practical uses haven't...

Pilot Mental Health, Methodologies, and Findings: A Systematic Review.

Pilots' mental health has received increased attention following Germanwings Flight 9525 in 2015, where the copilot intentionally crashed the aircraf...

[ST segment morphological classification based on support vector machine multi feature fusion].

ST segment morphology is closely related to cardiovascular disease. It is used not only for characterizing different diseases, but also for predicting...

Constructive Fuzzy Cognitive Map for Depression Severity Estimation.

Depression is a common and serious medical disorder that negatively affects the mood and the emotions of people, especially adolescents. In this paper...

Burnout and Depression Detection Using Affective Word List Ratings.

Burnout syndrome and depression are prevalent mental health problems in many societies today. Most existing methods used in clinical intervention and ...

Death by Robots? Automation and Working-Age Mortality in the United States.

The decline of manufacturing employment is frequently invoked as a key cause of worsening U.S. population health trends, including rising mortality du...

Resampling to address inequities in predictive modeling of suicide deaths.

OBJECTIVE: Improve methodology for equitable suicide death prediction when using sensitive predictors, such as race/ethnicity, for machine learning an...

Natural language processing of medical records: new understanding of suicide ideation by dementia subtypes.

Translating promise into practice: a review of machine learning in suicide research and prevention.

In ever more pressured health-care systems, technological solutions offering scalability of care and better resource targeting are appealing. Research...

Major depression disorder diagnosis and analysis based on structural magnetic resonance imaging and deep learning.

Major depression disorder is one of the diseases with the highest rate of disability and morbidity and is associated with numerous structural and func...

Designing Depression Screening Chatbots.

Advances in voice recognition, natural language processing, and artificial intelligence have led to the increasing availability and use of conversatio...

Predicting Sex-Specific Nonfatal Suicide Attempt Risk Using Machine Learning and Data From Danish National Registries.

Suicide attempts are a leading cause of injury globally. Accurate prediction of suicide attempts might offer opportunities for prevention. This case-c...

The quantification and clinical analysis of depression and anxiety in patients undergoing Da Vinci robot-assisted radical gastrectomy and open radical gastrectomy.

The purpose of paper is to investigate the depression and anxiety as well as independent influential factors between patients who underwent Da Vinci r...

Deep 3D-CNN for Depression Diagnosis with Facial Video Recording of Self-Rating Depression Scale Questionnaire.

The Self-Rating Depression Scale (SDS) questionnaire is commonly utilized for effective depression preliminary screening. The uncontrolled self-admini...

Discriminating Heterogeneous Trajectories of Resilience and Depression After Major Life Stressors Using Polygenic Scores.

IMPORTANCE: Major life stressors, such as loss and trauma, increase the risk of depression. It is known that individuals show heterogeneous trajectori...

Semi-supervised random forest regression model based on co-training and grouping with information entropy for evaluation of depression symptoms severity.

Semi-supervised learning has always been a hot topic in machine learning. It uses a large number of unlabeled data to improve the performance of the m...

Identification of Suicide Attempt Risk Factors in a National US Survey Using Machine Learning.

IMPORTANCE: Because more than one-third of people making nonfatal suicide attempts do not receive mental health treatment, it is essential to extend s...

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

IMPORTANCE: Diverse models have been developed to predict psychosis in patients with clinical high-risk (CHR) states. Whether prediction can be improv...